Polarisation-based coincidence event discrimination: an in silico study towards a feasible scheme for Compton-PET
Abstract
Current positron emission tomography (PET) systems use temporally localised coincidence events discriminated by energy and time-of-flight information. The two annihilation photons are in an entangled polarisation state and, in principle, additional information from the polarisation correlation of photon pairs could be used to improve the accuracy of coincidence classification. In a previous study, we demonstrated that in principle, the polarisation correlation information could be transferred to an angular correlation in the distribution of scattered photon pairs in a planar Compton camera system. In the present study, we model a source-phantom-detector system using Geant4 and we develop a coincidence classification scheme that exploits the angular correlation of scattered annihilation quanta to improve the accuracy of coincidence detection. We find a [Formula: see text] image quality improvement in terms of the peak signal-to-noise ratio when scattered coincidence events are discriminated solely by their angular correlation, thus demonstrating the feasibility of this novel classification scheme. By integrating scatter events (both single-single and single-only) with unscattered coincidence events discriminated using conventional methods, our results suggest that Compton-PET may be a promising candidate for optimal emission tomographic imaging.
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Evidence Hub reads this as a new method / technique, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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